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Seasonal variation of heavy metals in Subarnarekha River at Jamshedpur, East Singhbhum, Jharkhand
ANJU KUMARI, RAVINDER SINGH and N. G. GOSWAMI1
1CSIR-National Metallurgical Laboratory, Jamshedpur, Jharkhand, India-831007
Abstract :
current water quality standard along the Subarnarekha river in Jharkhand. Three samples were collected along the stretches of Subarnarekha basin during the period : Jan-Dec, 2015, on the first week of every month. The concentrations Cu, Pb, Ni, Zn, Cr, Co, Sr, Cd and Fe were determined using inductively coupled plasma mass spectrometry for seasonal fluctuation, source apportionment and heavy metal pollution indexing. The results demonstrated that concentrations of the metals showed significant seasonality. To assess the composite influence of all the considered metals on the overall quality of the water, heavy metal pollution indices were calculated. The deterioration of water quality and enhanced concentrations of certain metals in the Subarnarekha River near industrial and mining establishments may be attributed to anthropogenic contribution from the industrial and mining activities of the area. Various physicochemical parameters like pH, TDS, EC, DO, BOD, Total Hardness, Total alkalinity sodium, potassium, calcium, magnesium etc. were also analysed. Eight parameters namely pH, Dissolved Oxygen, Biochemical Oxygen Demand, Nitrate, Phosphate, Total Dissolved Solids and Faecal Colliform were considered to compute Water Quality Index (WQI) based on National Sanitation Foundation studies and discussed.
Keywords : Heavy metals, Subarnarekha river, NSF water quality index, TDS, EC, DO, BOD, Total hardness.
INTRODUCTION
River Water quality monitoring is necessary especially where the water serves as drinking water sources and threatened by pollution resulting from various human activities along the river course (Ahmad et al. 2010; Amadi 2011). Heavy metals contamination in river is one of the major quality issues in many fast growing cities, because maintenance of water quality and sanitation infrastructure did not increase along with population and urbanization growth especially for the developing countries (Karbassi et al. 2007; Akoto et al. 2008;
Ahmad et al. 2010). Metals enter into river from variety of sources; it can be either natural or anthropogenic (Wong et al. 2003; Adaikpoh et al. 2005; Akoto et al. 2008). Identification and quantification of these sources should form an important part of managing land and water resources within a particular river catchment (Bellos and Swaidis 2005).
Simultaneously, seasonal variations in agricultural activity, stormwater runoff, interflow and atmospheric deposition have strong effects on river water quality (Singh et al. 2004;
Ouyang et al. 2006; Cidu and Biddau 2007). Thus, characterization of seasonal variability in surface water quality is imperative for evaluating temporal variations of river pollution from natural or anthropogenic contributions.
Usually in unaffected environments, the concentration of most of the metals is very low and is mostly derived from the mineralogy and the weathering (Karbassi et al. 2008). Main anthropogenic sources of heavy metal contamination are mining, disposal of untreated and
PG Deptt., Kolhan University, Chaibasa, Jharkhand, India-833202
The present investigation is aimed at assessing the amount of heavy metals and
*Corresponding Authors Email : ngg1@rediffmail.com
partially treated effluents containing toxic metals as well as metal chelates from different industries and indiscriminate use of heavy metal-containing fertilizer and pesticides in agricultural fields (Ammann et al. 2002; Nouri et al. 2006, 2008). Rivers in urban areas have also been associated with water quality problems including metal contamination due to the practice of discharging of untreated domestic and small-scale industrial effluent into the water bodies (Rim-Rukeh et al. 2006; Khadse et al. 2008; Juang et al. 2009; Venugopal et al. 2009;
Sekabira et al. 2010).
However, in recent years much attention has been given towards the evaluation of heavy metal pollution in ground and surface waters with development of heavy metal pollution index (HPI) (Reddy 1995; Mohan et al. 1996). The metals monitored for the assessment of the water quality of any system give an idea of the pollution with reference to that particular metal only. HPI is a method that rates the aggregate influence of individual heavy metal on the overall quality of water and is useful in getting a composite influence of all the metals on overall pollution. In the HPI, a similar approach is adopted as Horton (1965) and NSFWQI. However, the weighted factors of the metals correspond to the inverse of the recommended standard of the metal and the summation of the weighted factors does not equal to 1. Moreover, in HPI higher values indicate deteriorated water quality with respect to metals as opposed to other WQI where higher values represent the better quality. In contrast to other WQI, where sub-indices are calculated using only standard values, HPI uses both the ideals values and the standard values.
MATERIALS AND METHODS Site Description
The study is carried out in Subarnarekha River which flows through the East Singhbhum district, which is one of the India's important industrialized areas known for ore mining, steel production, power generation, cement production and other related activities. The Subarnarekha river is the eighth river in India by its flow (12.37 billion m3/year) and length. The River Subarnarekha is a rain fed river originating near Nagri village (2301810211 N, 8501110411 E) in the Ranchi district, runs through several major cities and towns such as Ranchi, Muri, Jamshedpur, Ghatshila, Adityapur etc covering a distance about 400 km.
It finally joins the Bay of Bengal at Kirtania Port(2103311811 N, 8702313211 E) in Odisha.
Before falling in to the Bay of Bengal the River flows through Ranchi, Saraikela and East Singhbhum district of Jharkhand, West Midnapur district of West Bengal and Balasore district
J. MET. MATER SC., Vol. 58, No. 3, 2016 161 of Odisha. Of its total length 269 km are in Jharkhand, 64 km in West Bengal and 62 km in Odisha. The Subarnarekha basin covers an area 19,300 km2. This area is nearly the 0.6% of the total national river basin area and yields 0.4% of the country's total surface water resources. The climate of the study area is temperate. Annual rainfall is 1,200-1,400 mm.
This area is subject to the southwest monsoon and receives heavy rain (about 80%) during June-September (monsoon season). Its important tributaries include Kanchi, Karkari, Kharkai and Sankh rivers.
The water samples were grouped under following categories : S1 = Subarnarekha at Domohani
S2 = Subarnarekha at Mango Bridge S3 = Subarnarekha near Baridih Sampling and Analysis
Water samples were collected every month, from January 2015 to December 2015 from three different stations as mentioned below. In each site, three replicates were collected and subsequently mixed in situ. Water samples were collected in pre-conditioned acid-washed high-density polyethylene (HDPE) containers. The samples were filtered through pre-washed 0.45µmMillipore nitrocellulose filters. The initial portion of the filtration was discarded to clean the membrane, and the following ones destined for metal determination were acidified to pH < 2 using suprapure nitric acid and then stored refrigerated in pre-cleaned HDPE bottles until analysis (Radojevic and Bashkin 1999).
The water samples were analysed in the CSIR-NML Jamshedpur using standard methods (APHA 2005). The pH and Dissolved Oxygen of water samples were measured immediately after sampling at the field itself. Samples were subjected to filtration before chemical analysis.
The determination of TDS was done by gravimetric process while the total hardness was carried out by EDTA complexometric titration method (APHA 2005).The Winkler's alkali iodide-azide method was followed for the estimation of DO and BOD. Nitrate was determined colorimetric procedure (APHA 2005).
Heavy Metal Pollution Index
The HPI represent the total quality of water with respect to heavy metals. The HPI is based on weighted arithmetic quality mean method and developed in two steps. First by establishing a
rating scale for each selected parameter giving weightage and second by selecting the pollution parameter on which the index is to be based. The rating system is an arbitrary value between 0 to 1 and its selection depends upon the importance of individual quality considerations in a comparative way or it can be assessed by making values inversely proportional to the recommended standard for the corresponding parameter (Horton 1965; Mohan et al. 1996). In computing the HPI, Prasad and Bose (2001) considered unit weightage (Wi) as a value inversely proportional to the recommended standard (Si ) of the corresponding parameter as proposed by Reddy (1995).
The drinking water standards for India (IS 2012)were used for the metals for the calculation of Wi, with the exception of Co and V for which IS (2012) does not provide a standard. Instead, the standards for Co by USEPA (USEPA 2002) and for V by Gerke et al. (2010) were used for the calculations. The HPI model (Mohan et al. 1996) is given by Eq. (1)
HPI = ...(1)
where Qi is the sub-index of the ith parameter. Wi is the unit weightage of the ith parameter and n is the number of parameters considered.
The sub-index (Qi) of the parameter is calculated by Eq. (2)
Qi = ×100 ...(2)
where Mi is the monitored value of heavy metal of ith parameter, Ii is the ideal value of the ith parameter and Si is the standard value of the ith parameter. The sign (?) indicates numerical difference of the two values, ignoring the algebraic sign. The critical pollution index of HPI value for drinking water as given by Prasad and Bose (2001) is 100. However, a modified scale using three classes has been used in the present study after Edet and Offiong (2002). The classes have been demarcated as low, medium and high for HPI values <15, 15-30 and >30, respectively.
RESULTS AND DISCUSSION
The parameters, their weightings, their classification and the corresponding numerical ranges are given in Tables 1 and 2 respectively.
Table 1 : NSF WQI Parameter and Weights
Parameters WQI Weight
Dissolved Oxygen 0.17
pH 0.12
BOD5 0.1
Nitrates 0.1
Total Phosphates 0.1
Temperature Change 0.1
Turbidity 0.08
Total Solids 0.08
Table 2 : WQI Value Ranges (From Mitchell and Stapp, 1995)
Classification WQI Range
Very Bad 0-25
Bad 26-50
Medium 51-70
Good 71-90
Excellent 91-100
Σ
ni=1WiQiΣ
ni=1WiΣ
ni=1{Mi( )li}
(Si li)
−
−
J. MET. MATER SC., Vol. 58, No. 3, 2016 163 Table 3 : Physiochemical Parameters in Subarnarekha River
Parameters S1= Subarnarekha at S2= Subarnarekha near S3 = Subarnarekha near
Domohani Mango Bridge Baridih
Min Max Mean Min Max Mean Min Max Mean
PH 7.3 8.0 7.57 7.1 7.7 7.49 6.9 7.5 7.30
Turbidity 2.4 520 103.57 1.4 490 128.5 28.6 560 156.0
Total Solids 143 650.6 279.1 130 195 147.9 149.5 754 389.45
DO 2.0 8.9 6.06 4.8 7.0 6.00 0.0 7.6 3.23
BOD 0.4 39.6 4.48 0.3 2.2 1.09 0.4 59.8 17.35
Total 0.01 0.16 0.05 0.01 0.14 0.06 0.02 0.24 0.06
Phosphate
Nitrate 0.36 1.94 0.80 0.12 0.83 0.43 0.32 1.38 0.51
WQI 49 78 70 68 78 73 40 73 56
Table 4 : Monthly Water Quality Index at Domohani in Subarnarekha River
Parameters Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 PH 7.3 7.6 7.4 7.3 7.3 7.6 7.8 7.7 8.0 7.9 7.5 7.5 Turbidity 8.2 2.4 2.8 3.2 2.7 32.4 122.6 520 320 180 36.2 12.4 Total Solids 214.5 279.5 318.5 650.5 474.5 487.5 143 111.2 143 169 169 188.5
DO 7.0 6.2 3.2 5.8 7.0 2.0 6.0 5.8 6.8 6.2 7.9 8.9 BOD 2.0 3.0 0.4 0.4 2.0 39.6 1.8 0.6 1.2 0.4 0.8 1.6 Total 0.01 0.16 0.02 0.04 0.01 0.04 0.08 0.01 0.06 0.12 0.02 0.01 Phosphate
Nitrate 0.84 1.94 0.78 0.92 1.10 0.46 0.52 0.52 0.38 0.36 0.82 0.98
WQI 74 71 68 71 73 49 68 69 70 68 76 78
Classification Good Good Med Good Good Bad Med Med Good Med Good Good Table 5 : Monthly Water Quality Index Near Mango Bridge in Subarnarekha River
Parameters Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 PH 7.3 7.5 7.6 7.4 7.3 7.7 7.7 7.5 7.5 7.7 7.6 7.1 Turbidity 8.6 2.8 1.4 1.8 1.6 34.6 180 360 490 360 82 18.6 Total Solids 156 162.5 175.5 156 169 162.5 149.5 136.7 130 130 175.5 195 DO 7.2 6.4 6.4 6.2 4.8 5.4 6.8 4.8 6.0 7.0 5.0 6.0 BOD 0.6 0.8 1.0 2.0 0.6 2.2 1.0 0.8 2.0 0.4 0.8 1.2 Total 0.12 0.14 0.08 0.06 0.04 0.01 0.02 0.01 0.04 0.08 0.06 0.01 Phosphate
Nitrate 0.76 0.64 0.46 0.32 0.28 0.28 0.32 0.24 0.12 0.18 0.78 0.83
WQI 78 76 78 76 73 69 73 68 70 75 69 73
Classification Good Good Good Good Good Med Good Med Good Good Med Good
Table 6 : Monthly Water Quality Index Near Baridih in Subarnarekha River
Parameters Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 PH 6.9 7.4 7.5 7.2 7.4 7.4 7.5 7.4 7.0 7.7 7.0 7.2 Turbidity 28.6 36.1 47.2 30.2 29.4 152 280 560 362 260 48.6 38.2 Total Solids 169 520 754 520 175.5 650 520 559 253.5 149.5 208 195 DO 6.0 4.0 0.0 0.0 1.2 0.0 2.8 0.0 3.0 6.6 7.6 7.6 BOD 1.8 1.6 0.4 20.0 0.4 59.8 19.9 60.0 40.0 0.8 2.0 1.6 Total 0.14 0.08 0.06 0.06 0.01 0.02 0.02 0.01 0.06 0.04 0.08 0.08 Phosphate
Nitrate 0.68 0.52 0.46 0.42 0.51 0.32 0.47 0.68 0.12 0.43 0.80 0.71
WQI 69 59 53 44 61 40 44 40 47 71 71 73
Classification Med Med Med Bad Med Bad Bad Bad Bad Good Good Good Table 7 : Average Concentration of Heavy Metals in Surface water (µg/l) of
River Subarnarekha (Each Value in average of five Samples)
Location Cu Pb Ni Zn Cr Co Sr
A B C A B C A B C A B C A B C A B C A B C
Study 18.0 17.4 17.2 ND ND ND 2.2 2.8 2.02 18.2 14.2 12.8 1.90 1.84 1.78 0.96 0.88 0.76 35 34 33.8 Area 1
Study 18.8 17.8 17.4 ND ND ND 1.98 1.81 1.46 18.8 17.0 16.0 2.10 1.92 1.88 1.08 0.90 0.82 36.2 34 32 Area 2
Study 18.0 18.0 17.8 ND ND ND 3.82 2.98 2.46 20.6 18.6 14.8 2.04 2.00 1.80 1.02 0.92 0.80 37.8 34.6 29.8 Area 3
A= April' 15, B= July'15, C= Oct'15, N D = Not Detected
Table 8 : Average Concentration of Heavy Metals in Sediment sample (µg/g) of River Subarnarekha (Each Value in average of five Samples)
Location Cu Pb Ni Zn Cr Co Sr Cd Fe
A B C A B C A B C A B C A B C A B C A B C A B C A B C
Study 88 82 78.0 86 74 86 42 38 40 884 776.2 668 70.2 68.2 66.4 12.6 11.4 10.2 32.0 28.8 27.8 1.02 0.84 0.88 24 22 20
Area 1 22 47 24
50 26 32
Study 86 84 78.0 88 78 79 44 39 34 798 782 704 80.6 78.4 66.6 13.0 11.2 10.0 30.0 27.6 25.4 0.88 0.74 0.72 23 23 20
Area 2 21 01 01
40 90 20
Study 89 85 78.5 84 72 70 40 36.4 31.2 845 792 720 82.0 78.0 68.0 12.8 10.5 9.8 31.8 27.8 25.6 1.08 0.88 0.78 24 23 20
Area 3 61 24 10
21 10 40
A= April' 15, B= July'15, C= Oct'15, N D = Not Detected
Table 9 : HPI values of surface water of the Subarnarekha River for the different locations Code Sampling Site
S1 Domohani 21.47 8.83 9.60
S2 Near Mango Bridge 22.93 9.96 5.93
S3 Near Baridih 26.37 9.51 11.21
CONCLUSION
High values of TDS during rainy seasons may be due to massive soil erosion. The poor water quality of Subarnarekha River near Baridih is due to the improper treatment of the effluents from Jamshedpur steel plant. The prime duty of the educated public should be to spread
awareness in the rural as well as the urban areas. City drains connecting the safety tanks should not be allowed to directly fall in to the river. Proper treatment of the solid wastes should be made especially in urban areas. Deforestation should be strictly checked to control soil erosion due to which the TDs and Turbidity increases significantly during monsoon. Above all a long term action plan and online monitoring is a must to ensure the river water quality (Mitchell et al; 1995)
Concentrations of dissolved metals (Cu, Pb, Ni, Zn, Cr, Co, Sr, Cd and Fe) in the surface water of the Subarnarekha River demonstrated great seasonality. Irrespective of the locations, the elemental concentrations were lower in rainy monsoon season as compared to the other seasons due to pronounced dilution effect. When compared to drinking water guidelines established by WHO, India and the USEPA, much greater attention should be paid to Cu, Fe, Ni and Se though the concentrations were below the critical values in the monsoon season for some elements. The higher values of metals in the rivers imply additional inputs from unusual geochemical enrichment, which in turn may be attributed to the geological sources coupled with anthropogenic inputs from the catchments. The same is depicted in the calculated HPI also. The HPI ranged from 3.55 to 388.9 with an average of 32.27, falling in the high class. High HPI were observed at few locations near to industries, mining and the estuary. All the other locations fall under low to medium classes of HPI.
Thus, it is reasonably justified to conclude that the augmented concentrations of metals in water of the Subarnarekha River is greatly influenced by direct discharge of industrial, urban and mining.
REFERENCES
[1] Adaikpoh E.O., Nwajei G.E. and Ogala J.E., (2005), Heavy metals concentrations in coal and sediments from river Ekulu in Enugu, Coal City of Nigeria. J Appl Sci Environ Manag, 9(3), pp. 5-8.
[2] Ahmad M.K., Islam S., Rahman S., Haque M.R. and Islam M.M., (2010), Heavy metals in water, sediment and some fishes of Buriganga River, Bangladesh. Int J Environ Res., 4(2), pp. 321-332.
[3] Akoto O., Bruce T.N. and Darko G., (2008), Heavy metals pollution profiles in streams serving the Owabi reservoir. Afr J Environ Sci Technol, 2(11), pp. 354-359.
[4] Amadi A.N., (2011), Assessing the Effects of Aladimma dumpsite on soil and groundwater using water quality index and factor analysis. Aust J Basic Appl Sci., 5(11), pp. 763-770.
[5] Ammann A.A., Michalke B. and Schramel P., (2002), Speciation of heavy metals in environmental water by ion chromatography coupled to ICP-MS. Anal Bioanal Chem., 372(3), pp. 448-452.
[6] Bellos D. and Swaidis T., (2005), Chemical pollution monitoring of the River Pinios Thessalia- Greece. J Environ Manag, 76, pp. 282-292.
[7] Cidu R. and Biddau R., (2007), Transport of trace elements under different seasonal conditions:
effects on the quality of river water in a Mediterranean area. Appl Geochem, 22, pp. 2777-2794 123.
[8] Edet A.E. and Offiong O.E., (2002), Evaluation of water quality pollution indices for heavy metal contaminationmonitoring.Astudy case from Akpabuyo-Odukpani area, Lower Cross River Basin (southeastern Nigeria). GeoJournal, 57, pp. 295-304.
[9] Gerke T.L., Scheckel K.G. and Maynard J.B., (2010), Speciation and distribution of vanadium in drinking water iron pipe corrosion by-products. Sci Total Environ, 408, pp. 5845-5853.
[10] Horton R.K., (1965), An index number system for rating water quality. J Water Pollut Control Federation, 37(3), pp. 300-306.
[11] Juang D.F., Lee C.H. and Hsueh S.C., (2009), Chlorinated volatile organic compounds found near the water surface of heavily polluted rivers. Int J Environ Sci Technol, 6(4), pp. 545-556.
[12] Karbassi A.R., Monavari S.M., Nabi Bidhendi G.R., Nouri J. and Nematpour K., (2008), Metal pollution assessment of sediment and water in the Shur River. Environ Monitor Assess, 147(1-3), pp. 107-116.
[13] Karbassi A.R., Nouri J. and Ayaz G.O., (2007), Flocculation of trace metals during mixing of Talar river water with Caspian Seawater. Int J Environ Res., 1(1), pp. 66-73.
[14] Khadse G.K., Patni P.M., Kelkar P.S. and Devotta S., (2008), Qualitative evaluation of Kanhan river and its tributaries flowing over central Indian plateau. Environ Monitor Assess, 147(1-3), pp. 83 92.
J. MET. MATER SC., Vol. 58, No. 3, 2016 165
[15] Mitchell M.K. and Stapp W.B., (1995), Field Manual for Water Quality Monitoring. An Environmental education Programme for Schools Nineth edition. Green Project, Ann Arbor, MI, pp. 272.
[16] Mohan S.V., Nithila P. and Reddy S.J., (1996), Estimation of heavy metal in drinking water and development of heavy metal pollution index. J Environ Sci Health A, 31(2), pp. 283-289.
[17] Nouri J., Mahvi A.H., Babaei A. and Ahmadpour E., (2006), Regional pattern distribution of groundwater fluoride in the Shush aquifer of Khuzestan County Iran Fluoride. Fluoride, 39(4), pp.
321-325.
[18] Nouri J., Mahvi A.H., Jahed G.R. and Babaei A.A., (2008), Regional distribution pattern of groundwater heavy metals resulting from agricultural activities. Environ Geol., 55(6), pp. 1337.
[19] Prasad B. and Bose J.M., (2001), Evaluation of heavymetal pollution index for surface and spring water near a limestone mining area of the lower Himalayas. Environ Geol., 41, pp. 183-188.
[20] Radojevic M. and Bashkin V.N., (1999), Practical environmental analysis. Royal Society of Chemistry, London.
[21] Reddy S.J., (1995), Encyclopaedia of environmental pollution and control, Environmental Media, Karlia, 1, pp. 342.
[22] Rim-Rukeh A., Ikhifa O.G. and Okokoyo A.P., (2006), Effects of agricultural activities on the water quality of Orogodo River, Agbor Nigeria. J Appl. Sci. Res., 2(5), pp. 256-259.
[23] Sekabira K., Oryem-Origa H., Basamba T.A., Mutumba G. and Kakudidi E., (2010), Assessment of heavy metal pollution in the urban stream sediments and its tributaries. Int J Environ Sci Technol., 7(3), pp. 435- 446.
[24] Singh K.P., Malik A., Mohan D. and Sinha S., (2004), Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)-a case study.
Water Res., 38, pp. 3980-3992.
[25] Venugopal T., Giridharan L. and Jayaprakash M., (2009), Characterization and risk assessment studies of bed sediments of River Adyar-an application of speciation study. Int J Environ Res., 3(4), pp. 581-598.
[26] Wong C.S.C., Li X.D., Zhang G., Qi S.H. and Peng X.Z., (2003), Atmospheric deposition of heavy metals in the Pearl River Delta. China. Atmos Environ., 37(6), pp. 767-776.
